---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: unispeech-sat-base-digit-mask-ft
  results: []
datasets:
- mazkooleg/digit_mask_augmented_raw
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# unispeech-sat-base-digit-mask-ft

This model is a fine-tuned version of [microsoft/unispeech-sat-base](https://huggingface.co/microsoft/unispeech-sat-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0053
- Accuracy: 0.9991
- F1: 0.9991

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Accuracy | F1     | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|
| 0.0079        | 1.0   | 14264 | 0.9991   | 0.9991 | 0.0053          |
| 0.0019        | 2.0   | 28528 | 0.9987   | 0.9987 | 0.0078          |
| 0.0009        | 3.0   | 42792 | 0.9989   | 0.9989 | 0.0069          |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.13.0+cpu
- Datasets 2.12.0
- Tokenizers 0.13.2